AI-Driven Cyber-Risk Dashboard for Small and Medium Enterprises (SMEs) in Oil and Gas Sector

Oil and gas supply-chain SMEs that support the oil and gas sector are highly vulnerable to cyber threats, yet no systematic maturity assessment tool exists for this sector. This paper presents an AI-driven Cyber-Risk Dashboard that integrates (i) a data-driven Cyber-Maturity Score (CMS) predicting incident likelihood, (ii) a multilingual Transformer-based phishing detector and policy-compliance checker, and (iii) real-time Media-Monitoring Analytics (MMA) that surface coordinated misinformation and emerging threat narratives. We deployed a sequential explanatory mixed-methods study: (1) a 400-unit survey, (2) 30 in-depth interviews, (3) machine-learning model development, (4) MMA dashboard construction, and (5) validation on five SMEs. The CMS achieved an AUC = 0.87 against historical incident logs; the BERT-based phishing model attained 94 % precision and reduced false-positive rates by 32 % relative to rule-based baselines. MMA alerts shortened average incident detection time by 46 %. The integrated dashboard enabled SMEs to move from “unknown” to “low-risk” tiers within 14 days, and provided oil and gas companies’ procurement teams with a risk-based supplier-screening platform. We discuss implications for SME resilience, oil and gas companies’ supply-chain continuity, and regulatory support under the Saudi Personal Data Protection Law (PDPL). Limitations and future research directions are outlined.